Literature DB >> 18977103

CAD in questions/answers Review of the literature.

Bruno Boyer1, Corinne Balleyguier, Olivier Granat, Christian Pharaboz.   

Abstract

Generalization of breast screening programs requires an efficient double reading of the mammograms, which allows reduction of false-negative rate, but might be difficult to organize. CAD (Computed Assisted Diagnosis) is dramatically improving and is able to detect suspicious mammographic lesions, either suspicious microcalcifications, masses or architectural distorsions. CAD mammography might complete or substitute to "human" double reading. The aim of this review is to describe major CAD systems commercially available, working of CAD and to present principal results of CAD mammography. Specially, place of CAD within breast screening program, according to the results of recent prospective studies will be discussed.

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Mesh:

Year:  2008        PMID: 18977103     DOI: 10.1016/j.ejrad.2008.07.042

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  7 in total

1.  Radiological technologists' performance for the detection of malignant microcalcifications in digital mammograms without and with a computer-aided detection system.

Authors:  Rie Tanaka; Miho Takamori; Yoshikazu Uchiyama; Junji Shiraishi
Journal:  J Med Imaging (Bellingham)       Date:  2015-05-27

2.  Using breast radiographers' reports as a second opinion for radiologists' readings of microcalcifications in digital mammography.

Authors:  R Tanaka; M Takamori; Y Uchiyama; R M Nishikawa; J Shiraishi
Journal:  Br J Radiol       Date:  2014-12-23       Impact factor: 3.039

3.  Open access image repositories: high-quality data to enable machine learning research.

Authors:  F Prior; J Almeida; P Kathiravelu; T Kurc; K Smith; T J Fitzgerald; J Saltz
Journal:  Clin Radiol       Date:  2019-04-28       Impact factor: 2.350

4.  Mammographic image denoising and enhancement using the Anscombe transformation, adaptive wiener filtering, and the modulation transfer function.

Authors:  Larissa C S Romualdo; Marcelo A C Vieira; Homero Schiabel; Nelson D A Mascarenhas; Lucas R Borges
Journal:  J Digit Imaging       Date:  2013-04       Impact factor: 4.056

Review 5.  CAD and AI for breast cancer-recent development and challenges.

Authors:  Heang-Ping Chan; Ravi K Samala; Lubomir M Hadjiiski
Journal:  Br J Radiol       Date:  2019-12-16       Impact factor: 3.039

6.  Bayesian classifier with simplified learning phase for detecting microcalcifications in digital mammograms.

Authors:  Imad Zyout; Ikhlas Abdel-Qader; Christina Jacobs
Journal:  Int J Biomed Imaging       Date:  2010-01-04

Review 7.  Is single reading with computer-aided detection (CAD) as good as double reading in mammography screening? A systematic review.

Authors:  Edward Azavedo; Sophia Zackrisson; Ingegerd Mejàre; Marianne Heibert Arnlind
Journal:  BMC Med Imaging       Date:  2012-07-24       Impact factor: 1.930

  7 in total

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